Environmental Engineering Reference
DG-AGRI and other studies in an estimation framework which mutually ensures
compatibility of the different forecasted elements (such as crop areas and herd
sizes, yields and other output coefficients, productions and different elements of
product demand, see Britz et al. 2007) .
Graphical User Interface
The technical realization of CAPRI changed over the last decade, and is, after
quite some changes, by now based on a Graphical User Interface (GUI) realised in
JAVA and GAMS, without a separate DataBase Management System (DBMS).
Interestingly, a policy editor was realized in a very early version, but later abandoned
as it was hard to maintain in a period of rapidly evolving policy instruments. Instead,
a much more complex policy description was directly introduced in GAMS in order
to capture, as close as possible, the changing agricultural policy. This solution
clearly allows for a greater degree of flexibility, but in-depth knowledge about
the representation of the various policy instruments in the code is required to
successfully implement scenarios.
The CAPRI GUI is mainly developed as a tool to support trained users in
result exploitation and model application, including building up the database and
model calibration. It could therefore be called an expert GUI. To exploit results,
data and model results including those from indicator calculators are stored in
one possible very large, sparse multi-dimensional cube. Result tables (such as
prices, market balances, and environmental indicators), maps or graphs are
generated as reports (or “views”) from these cubes. Each view applies specific
filters and shows the resulting extraction in a specific presentation (table, graph or
map). Views are linked to each other, allowing for a kind of drill-down approach by
going from more general or aggregate results to more detailed ones. General tables
of aggregated indicators give an overview of the main scenario impacts, and can be
directly used for reports. Highly detailed technical tables show relevant information
for a more refined analysis of the results or for modellers to use during the model
debugging process (e.g. convergence statistics or dual values of the optimisation
models for each activity and region).
The SEAMLESS-IF GUI is more oriented towards policy assessment and
supports the user in all stages of the policy assessment (from the definition of
a storyline to the analysis of model results by means of exploitation tools).
Moreover, SEAMLESS-IF manages a wider range of components compared to
CAPRI and supports the integrative modeller in scenario development and
selection of the model chain (pre-modelling-phase). The policy expert is given
less functionality and is restricted mainly to view results (post-modelling phase).
The exploitation tools are based on client-server solutions providing a limited
number of visualisation possibilities for preselected indicators and model variables
(see Chapter 9).